方法对比
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| 多群体收敛效度× | 验证性因子分析（CFA）× | |
|---|---|---|
| 领域 | 心理测量学 | 心理测量学 |
| 方法族 | Latent structure | Latent structure |
| 起源年份≠ | 1981 / 2000 | 1969 |
| 提出者≠ | Fornell & Larcker (convergent validity criteria); Vandenberg & Lance (multi-group extension) | Karl Gustav Jöreskog |
| 类型≠ | Validity assessment procedure | Hypothesis-testing latent variable model |
| 开创性文献≠ | Fornell, C. & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. DOI ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| 别名 | cross-group convergent validity, multi-sample convergent validity, MGCFA convergent validity, AVE across groups | CFA, confirmatory FA, measurement model, restricted factor analysis |
| 相关≠ | 6 | 4 |
| 摘要≠ | Multi-group convergent validity examines whether items purported to measure the same latent construct relate strongly to that construct consistently across distinct subgroups such as demographic categories, cultures, or experimental conditions. It extends single-sample convergent validity checks into a comparative multi-group confirmatory factor analysis framework. | Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing. |
| ScholarGate数据集 ↗ |
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